WPS6615
Policy Research Working Paper 6615
Background Paper to the 2014 World Development Report
Benchmarking Financial Systems
Introducing the Financial Possibility Frontier
Thorsten Beck
Erik Feyen
The World Bank
Development Economics
Office of the Senior Vice President and Chief Economist
September 2013
Policy Research Working Paper 6615
Abstract
Across the world, supply for financial services rarely categorize different problems of shallow financial markets
matches the demand, given multiple market frictions. or unsustainable expansion. The paper offers three
This paper discusses the concept of the financial examples of how to use different data sources to apply the
possibilities frontier as a constrained optimum to frontier concept to assess the state of financial systems.
This paper—prepared as a background paper to the World Bank’s World Development Report 2014: Risk and Opportunity:
Managing Risk for Development—is a product of the Development Economics Vice Presidency. The views expressed in
this paper are those of the authors and do not reflect the views of the World Bank or its affiliated organizations. Policy
Research Working Papers are also posted on the Web at http://econ.worldbank.org. The authors may be reached at T.Beck@
tilburguniversity.edu and efeijen@worldbank.org.
The Policy Research Working Paper Series disseminates the findings of work in progress to encourage the exchange of ideas about development
issues. An objective of the series is to get the findings out quickly, even if the presentations are less than fully polished. The papers carry the
names of the authors and should be cited accordingly. The findings, interpretations, and conclusions expressed in this paper are entirely those
of the authors. They do not necessarily represent the views of the International Bank for Reconstruction and Development/World Bank and
its affiliated organizations, or those of the Executive Directors of the World Bank or the governments they represent.
Produced by the Research Support Team
Benchmarking Financial Systems:
Introducing the Financial Possibility Frontier
Thorsten Beck and Erik Feyen*
JEL codes: G1, G2, O4
Keywords: Financial development; financial fragility; financial sector policies
*Beck: Cass Business School, Tilburg University and CEPR; Feyen: World Bank. This
paper’s findings, interpretations, and conclusions are entirely those of the authors and do
not necessarily represent the views of the World Bank, its Executive Directors, or the
countries they represent.
2
1. Introduction
Households, enterprises and governments demand financial services to reallocate
consumption and investment across different time periods and different states of the
world. The fact that the financial sector is one of the oldest service sectors in human
history suggests that the demand for (i) payment, (ii) savings, (iii) credit, and (iv) risk
management services is a fundamental characteristic of exchange-based economies. 1
Micro-evidence in the form of financial diaries (Collins et al., 2009) has shown that even
the poorest of the poor have demand for financial services, even though this demand is
satisfied mostly by informal arrangements.
In spite of widespread demand for financial services, there is a high variation in the
range and depth of financial service provision across countries. This paper introduces the
concept of the possibility frontier, which is the constrained optimum of financial
development in an economy, as diagnostic tool to assess the gap between actual provision
of financial services and demand from the real sector and identify bottlenecks that prevent
further financial deepening of financial institutions and markets, on the one hand, and
mitigate risks of overheating in banking or capital markets, on the other hand. We will use
a cross-country benchmarking exercise to illustrate the application of the frontier concept.
We will then suggest several specific applications of the frontier concept. Specifically, we
will assess the performance of i) the transition economies in the 1990s and 2000s, ii)
illustrate the assessment of SME finance with firm-level data and iii) use the example of
Egypt to document the use of different data sources to gauge the development of its
financial system.
1
For just one example of historic financial arrangements and their development during the Roman empire
see Malmendier (2009).
3
It is important to distinguish between the different services provided by financial
institutions and markets. While the need for payment services is basic across all exchange-
based economies, though increasing with specialization and division of labor, the demand
for credit, savings, and risk management services is partly a function of the economic
environment in which households, enterprises and governments work. The high volatility
facing many low-income countries, related to volatile export prices – particularly for
commodity-based exporters – and natural calamities increases the demand for risk
management services. Given the high degree of informality and consequent volatility of
income flows for many households, there is need for financial products to mitigate the
impact of this income volatility and allow for smooth consumption patterns. Similarly,
extensive research has shown that the availability of long-term financing sources enables
firms to innovate more and invest in fixed assets (e.g. Aghion et al., 2009). Investment in
infrastructure, be it private or public, requires access to long-term financing sources.
Finally, effective monetary policy, adequate exchange rate management and fiscal policy
space rely on deep and liquid financial markets (IMF, 2012).
While the basic demand for financial services therefore does not systematically
vary with the level of income, different financial products and services are being
demanded in countries with different levels of income, by different educational and
occupational groups, and in different socio-economic circumstances. More importantly,
however, the supply of financial services varies systematically across countries of
different sizes and income levels, not just in depth and outreach, but also in the breadth
and diversity of institutions and markets, products and services. And low-income
countries, often with the highest need for financial markets to mitigate risks stemming
4
from volatility and shocks, suffer most from the dearth of the necessary financial
instruments and products. In addition, shallow financial systems in many low- and
middle-income countries drive a wedge between inherent and bankable, i.e. commercially
viable, demand, effectively excluding a large share of the population.
The literature has related an array of country characteristics to the level of financial
sector development, ranging from market structure and competition over broad
institutional characteristics and specific policies to historic factors. 2 The observed
aggregate volume of financial service provision and individual or enterprise use of
specific financial services, however, reflect as much supply as demand, and shallow
financial markets can be the result of demand-side as much as of supply-side constraints.
In this paper, we will abstract from historic factors and focus on policies,
incentives, and government interventions that can explain cross-country variation in
financial sector development. To better understand this variation, we will next introduce
the concept of a possibility frontier, which can be based on aggregate as on micro-level
considerations. This frontier denotes the constrained optimum of financial depth or the
share of population that can be commercially served in a sustainable manner, given
structural country characteristics, technological constraints, and long-term policy choices.
The frontier concept allows distinguishing between demand- and supply-side constraints
and a classification of policies according to whether they aim at shifting the frontier
outwards, moving closer to the frontier or at preventing the financial system from moving
beyond the frontier to an unsustainable point, which ultimately will end in fragility.
2
See Beck (2013) for a detailed discussion.
5
We will illustrate the use of the frontier concepts with several examples. First, we
will discuss a benchmarking exercise that relates aggregate indicators of financial sector
development to country characteristics to predict a structural depth line, i.e. the level of
financial depth predicted by socio-economic characteristics of the economy. While such a
structural depth line is not identical to the frontier concept, as it does not take into account
long-term policy variables, it is an important first approximation and can serve as basis for
cross-country and over-time comparisons of financial system development. We will also
use this benchmarking exercise to compare the development of different segments of the
financial system with country characteristics. Second, we will use the benchmarking
exercise and the example of the former transition economies to illustrate the relative
development of both structural depth line and actual levels of financial sector development
over the past twenty years. We will document the rapid deepening process across the
transition economies as well as the overheating after the mid-2000s. Third, we will
illustrate the application of the frontier concept to the SME market, using firm-level data
from the World Bank’s Enterprise Survey data. Such micro-data allow closer insights into
specific demand and supply-side constraints. Finally, we will use the example of a
specific country – Egypt – to illustrate how the combination of aggregate and micro-data
allows an assessment of underlying constraints to financial sector development. The
conclusion from these three specific examples is that a combination of macro and micro
data is necessary to determine not only the situation of a financial system or a specific
segment of the financial system relative to its frontier, but also to identify the specific
constraints.
6
While this paper relates directly to a small literature on the policies and institutions
underpinning sustainable financial development, it also relates to a much larger literature
on the relationship between financial deepening and economic development. While
extensive empirical work has shown a positive relationship between financial depth and
economic growth (see Levine, 2005, for an overview), recent work has pointed to
important non-linearities in this relationship or even a range of financial depth where this
relationship turns negative (Aghion et al., 2005; Arcand et al., 2012). This is in addition to
an extensive literature that has shown that rapid increases in credit are associated with a
higher likelihood of systemic banking distress (Demirguc-Kunt and Detragiache, 2005). 3
The remainder of this paper is structured as follows. The next section introduces
the concept of the financial possibility frontier. Section 3 uses the concept to discuss
different policy options for sustainable financial deepening. Section 4 introduces the
benchmarking exercise and section 5 uses the example of the transition economies to
illustrate its application. Section 6 discusses the access possibilities frontier for SMEs and
the use of Enterprise Surveys. Section 7 uses the example of Egypt to demonstrate the
need to use both aggregate and micro data. Section 8 concludes.
2. The financial possibility frontier
The section introduces the financial possibility frontier, a concept that builds on previous
work by Beck and de la Torre (2007) and Barajas et al. (2012).
3
For a discussion on how banking fragility has affected households in Eastern Europe, see Brown (2013).
7
2.1. Market frictions
In a world without market frictions, i.e. without transaction costs and information
asymmetries, and without uncertainty, direct financial transactions between savers and
borrowers would be feasible and there would be no need for financial institutions or
markets. Uncertain outcomes in a world with risk-averse agents put a premium on risk
diversification and create demand for risk management services. Information asymmetries
and limited enforceability of contracts give rise to agency problem. These agency
problems and transaction costs introduce additional market frictions, which ultimately
give rise to financial institutions and markets that can help overcome these frictions and
economize on costs. In addition to these “bilateral frictions”, collective frictions related to
network externalities and first-mover disadvantages can prevent the development of
financial markets that rely on depth and liquidity and cost-effective payment systems (De
la Torre and Ize, 2010, 2011).
While financial institutions and markets help overcome these market frictions, their
efficient operation is restricted by these same market frictions. The typical market
frictions that interact to affect the process of financial deepening are associated either with
information, enforcement, or transactions costs (Levine, 2005; Merton and Bodie, 2005;
De la Torre, Feyen and Ize, 2013). 4 Fixed transaction costs in financial service provision
result in decreasing unit costs as the number or size of transactions increases. 5 The
4
For the following, see a similar discussion in Beck and de la Torre (2007).
5
These fixed costs exist at the level of the transaction, client, institution, and even the financial system as a
whole. Processing an individual payment or savings transaction entails costs that, at least in part, are
independent of the value of the transaction. Similarly, maintaining an account for an individual client also
implies costs that are largely independent of the number and size of the transactions the client makes. At the
level of a financial institution, fixed costs span a wide range—from the brick-and-mortar branch network to
computer systems, legal and accounting services, and security arrangements—and are independent of the
number of clients served. Fixed costs also arise at the level of the financial system (e.g., regulatory costs
8
resulting economies of scale at all levels explain why financial intermediation costs are
typically higher in smaller financial systems and why smaller economies can typically
only sustain small financial systems (even in relation to economic activity). They also
explain the limited capacity of small financial systems to broaden their financial systems
towards clients with need for smaller transactions. In summary, fixed transaction costs can
explain the high level of formal financial exclusion in many developing countries. Fixed
costs can also explain the lack of capital markets in many small developing economies.
In addition to costs, the depth and outreach of financial systems, especially in
credit and insurance services, is constrained by risks, particularly default risk. These risks
can be either contract specific or systemic in nature. While idiosyncratic risks are specific
to individual borrowers, projects or policy holders, their management is influenced by the
systemic risk environment. High macroeconomic uncertainty and deficient contract
enforcement institutions exacerbate agency problems, while the lack of diversification
possibilities can hinder the ability of financial institutions to diversify non-agency risks.
As systemic risk increases, it enlarges the set of borrowers and projects that are effectively
priced out of credit and capital markets. Similarly, it makes insurance policies
unaffordable for larger segments of the population. At the same time, the easing of agency
frictions in the absence of adequate oversight can create incentives for excessive risk-
taking by market participants (by failing to internalize externalities), fueling financial
instability.
and the costs of payment, clearing, and settlement infrastructure) which are, up to a point, independent of the
number of institutions regulated or participating in the payment system.
9
2.2. State variables
The efficiency with which financial institutions and markets can overcome market
frictions is critically influenced by a number of state variables—factors that are invariant
in the short-term (often lying outside the purview of policy makers)—that affect provision
of financial services on the supply-side and can constrain participation on the demand-
side. In broad terms, we can distinguish between two types of state variables: (i) structural
characteristics of the socio-economic environment in which financial institutions and
markets operate and which impose a limit on their development and (ii) long-term policy
variables that either foster or limit financial deepening. While structural variables relate to
the broader socio-political and structural environment in which the financial system
operates, including market size, population distribution, demographic structure, policy
variables are often directly related to the financial sector, as, e.g., macroeconomic
fundamentals, the available technology, contractual and information frameworks
underpinning the financial system, and regulatory and supervisory frameworks. Among
the structural variables is the size of the market, as already discussed, which reduces the
possibilities to diversify and hedge risks, while at the same time increasing concentration
risks. Similarly, the demographic structure of the population can be important, as it
influences both savings behavior and demand for financial services. The geographic
structure of a country and population distribution can influence the costs of distributing
financial services. Finally, the income level itself, while certainly endogenous to the
development of the financial sector, as documented by an extensive literature, positively
affects the commercially viable demand and reduces the cost of financial service
provision. Higher levels of average income typically also come with higher levels of
10
institutional development and sophistication and higher levels of formal economic
activity, thus increasing the share of commercially viable clients.
Figure 1: Stylized Financial Possibility Frontier
Financial depth
Policy
0 0
0
Structural factors
2.3. The frontier
Using the concept of state variables allows us to define the financial possibility
frontier as a rationed equilibrium of optimal supply and demand, variously affected by
market frictions. In other words, this is the maximum sustainable depth (e.g., credit or
deposit volumes), outreach (e.g., share of population reached) or breadth of a financial
system (e.g., diversity of domestic sources of long-term finance, including banks, long-
term debt and equity markets, private equity companies, and different contractual savings
11
institutions) that can be realistically achieved at a given point in time. As we will discuss
below, the actual depth, outreach or breadth can vary from the frontier, for various
reasons. While they can stay below the frontier for longer time periods, it is unlikely that
a financial system can move beyond the frontier for a sustained period, especially in the
area of credit, without systemic bank fragility as this would suggest that risks are not
being properly priced or that the borrower population has been expanded beyond its
commercially viable maximum. In non-risk taking services, such as payment or saving
services, movements beyond the frontier can only be achieved through subsidies or
financial repression forcing the population into the banking system, though even here,
risks loom large as these resources might eventually find their way into risk taking,
through a shadow banking system.
Figure 1 illustrates the financial possibility frontier and the difference between
structural and policy variables among the state variables. We graph the frontier in a three-
dimensional space, where the x- and z-axes denote structural and policy state variables,
respectively, while the y-axis denotes financial development. All three axes are one-
dimensional representation of an array of variables. A movement outwards on the x-axis
indicates improvement in the structural state variables –e.g., size, demographic structure,
socio-political situation – conducive to financial deepening. Similarly, movements
outwards on the z-axis indicate improvements in long-term policies and institutions – e.g.,
macroeconomic stability, contractual framework – that are conducive for financial
deepening.
The plane indicates the financial possibility frontier, i.e. the level of financial
development sustainable in the long-term for a given combination of structural and policy
12
state variables. If the financial system is below the plane, this suggests that it has not
achieved the optimal level feasible under current demand- and supply-side constraints. A
financial system above the plane suggests an unsustainable level of financial deepening,
most likely to result in fragility. The split of state variables into structural and policy
variables also underlines the importance of taking into account structural constraints when
evaluating the potential for financial sector development. Put differently, policies and
institutions supporting sustainable financial development are even more important in
countries with very adverse structural characteristics.
2.4. Product specific frontiers
Conceptually, the frontier can vary for different types of financial services,
depending on the sources of market frictions. For instance, the frontier for payment and
savings services, where transaction costs are the decisive constraint, can be different from
that for credit and insurance services, where risk is an additional important component.
The financial possibility frontier can also move over time, as income levels change, the
international environment adjusts, new technologies arise, and the overall socio-political
environment in which financial institutions operate changes.
Depending on which dimension of financial development and on which segment of
the financial system one focuses, different relationships between state variables and the
frontier are predicted by theory. Scale is especially important for capital markets that rely
on liquidity and thus active trader bases, but also a sufficient supply of “marketable”
enterprises, i.e. enterprises at a scale and transparency to issue public securities. The
importance of monetary stability for defining the frontier increases in the maturity of the
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financial service. The dependence on the contractual framework is more important for
arms-length than relationship based financing contracting and thus more important for
corporate bond markets than for banks. Geographic dispersion of the population and the
quality of the infrastructure is especially important for the outreach of the financial
system. Different segments of the financial system, however, also depend on each other.
Insurance companies and pension funds depend on long-term investment opportunities,
such as traded and non-traded equity and debt securities. Banks rely on capital markets to
hedge risks and securitize assets. Mortgage finance relies on the availability of long-term
investors, such as pension funds and insurance companies.
In the context of developing countries, it is important to distinguish between
savings or resource constraints and intermediation constraints. 6 While demographic or
income constraints might limit the amount of resources available for financial
intermediation in the economy, most financial systems in low-income countries seem
rather intermediation constrained, i.e. banks are characterized by a large share of
investment in liquid and government securities. Relating to the discussion above, this
suggest that the liability side of banking (mobilization of savings and resources more
generally) might face lower constraints relating to state variables than the assets side,
especially private sector lending, which is often constrained by agency frictions
exacerbated by deficient contractual and information frameworks. Relaxing constraints on
the liability side might also involve different policies than relaxing constraints on the asset
side.
6
See similar arguments on a broader level by Hausman, Rodrik and Velasco (2005) in their discussion on
growth constraints.
14
2.5. The challenges for sustainable financial sector deepening
Generalizing from the above discussion, we can identify three broad challenges
facing countries. First, the financial possibility frontier may be low relative to countries at
similar levels of economic development due to deficiencies in state variables. Here we can
distinguish between the role played by structural and policy state variables. While policy
variables can be addressed with long-term institutional reforms, a low structural depth
frontier might require additional institutional reforms. Small scale might require countries
to tap the possibilities offered by globalization in terms of risk diversification and scale
economies. Countries with disperse population might have to rely more on technology and
non-branch delivery channels than other countries
Second, there is the possibility that a financial system lies below the frontier, i.e.
below the constrained maximum defined by state variables, due to demand and/or supply-
side constraints. Demand-side constraints can arise if, for instance, the number of loan
applicants is too low due to self-exclusion (e.g., due to lack of financial literacy) or on
account of a lack of viable investment projects in the economy (e.g., as a result of short-
term macroeconomic uncertainty). Supply-constraints influencing idiosyncratic risks or
those artificially pushing up costs of financial service provision might also serve to hold
the financial system below the frontier. 7 For instance, lack of competition or regulatory
restrictions might prevent financial institutions and market players from reaching out to
new clientele or introducing new products and services. Similarly, regulatory barriers can
7
It should be noted that lack of private sector participation could also result from other frictions in the
economy. For instance, barriers to doing business, tax distortions that discourage firm growth, directed
subsidies to industries and sectors, among others, are examples of distortions complementary to credit
market frictions which serve to constrain participation.
15
prevent deepening of certain market segments as can weak systems of credit information
sharing or opacity of financial information about firms.
Finally, the financial system can move beyond the frontier, indicating an
unsustainable expansion of the financial system beyond its fundamentals, i.e. an expansion
that is likely to end in systemic banking distress. For instance, “boom-bust” cycles in
economies can occur in the wake of excessive investment and risk taking (often facilitated
by loose monetary policy) by market participants. Experience from past banking crises
suggests that credit booms and subsequent busts typically occur in environments
characterized by poorly defined regulatory and supervisory frameworks. As underscored
by the global financial crisis, financial innovation and regulatory ease can foster rapid
deepening, but also pose challenges for financial stability. 8 Finally, fragility in many
developing countries is often linked to governance problems, so that an overshooting of
the financial possibility frontier may also be related to limited supervisory and market
discipline. 9
While the frontier concept implies a specific level of financial development for a
given combination of structural and policy state variables that is sustainable in the long-
run, risk-return preferences might vary across countries, as illustrated in Figure 2.
Societies might choose different points along the trade-off line between financial
deepening and stability, with more risk-loving societies choosing higher risk of fragility to
achieve a deeper financial system while other societies might prefer a more constrained
8
See Beck et al. (2012) for evidence on the bright and dark sides of financial innovation.
9
There might also be important interactions between the outreach of the financial system and its stability as
shown by Han and Melecky (2013) who show that countries with broader access to deposit services faced
lower probabilities of deposit withdrawals during the crisis.
16
financial system to benefit from higher stability. As in Figure 1, combinations of stability
and depth below the frontier are sub-optimal, while combinations above the frontier are
not feasible in this graph and trade-off.
Figure 2: Depth-Stability trade-off
Region where depth is too high, given
societal stability requirement.
Max depth, max risk
Depth Optimum
Optimal depth, given
Clearly suboptimal policy mix,
societal stability requirement
i.e. too little or too much of some
policies
No depth, no risk
Stability
Minimum stability
society requires -- a choice
It is important to understand that some of the policies can both help the financial
system move closer to the frontier and have the potential of pushing it beyond the frontier.
Competition is a very good example. Competition and contestability can facilitate the
entry of new players, the introduction of new products and new delivery channels and thus
push a financial system towards the frontier. In effect, competitive pressure and the search
for profits are key factors behind such examples of outreach as offering of services that are
tailor-made for low-income clients (e.g., simple debit accounts at lower costs than regular
checking accounts) or the use of mobile branches or cell phone banking to reach
populations in remote areas at low costs. At the same time, indiscriminate free entry for
17
new deposit-taking credit institutions or the intensification of competition among existing
institutions can lead to lending binges and fragility. A regulatory framework that allows
innovation, while at the same time avoiding excessive risk-taking, is therefore called for.
As shown by Beck, de Jonghe and Schepens (2013), the regulatory framework is critical
for the effect of bank competition on banks’ risk taking and fragility.
3. Using the frontier to define policy options for financial sector deepening
Identifying a country’s position relative to the financial possibility frontier is a first step
towards defining an adequate policy mix to achieve an optimum, long-term sustainable
level of financial sector development. In this section, we discuss three sets of policies that:
(i) push the frontier outwards (market-developing policies); (ii) push the system towards
the frontier (market-enabling policies); and (iii) prevent the financial system from moving
beyond the frontier (market-harnessing policies). It is important to stress that all these
policy areas focus on overcoming market frictions and market failures and aim at better
functioning markets. They stand in contrast to market-replacing policies that aim to
substitute market with government mechanisms. In the overwhelming majority of cases,
such mechanisms have not worked (Fry, 1988, La Porta et al., 2002).
Market-developing policies aim at pushing out the financial possibility frontier.
Such reforms include, for instance, legal (even constitutional) changes and substantial
upgrading of macroeconomic (particularly fiscal) performance. Cross-country
comparisons suggest that macroeconomic stability is critical for financial deepening
(Boyd, Levine and Smith, 2001), while country experiences suggest that macroeconomic
18
stability is a necessary condition for unlocking the financial deepening process. 10 Smaller
countries are less likely to be hosts to thriving financial systems as they lack the necessary
scale for a diversified, competitive landscape of institutions and markets (need reference).
Accessing the vast risk-pooling and diversification opportunities offered by international
capital markets, while adopting appropriate macro-prudential policies to dampen the
impact of potentially disruptive volatile international capital flows, can be important for
such economies. Constraints imposed by market size can be partly overcome through
regional integration and foreign bank entry, although risks have to be carefully managed,
as evidenced by the global financial crisis. An extensive literature has shown that
strengthening informational and contractual frameworks (e.g., building or upgrading of
credit registries, collateral, risk insurance) and providing supporting market infrastructure
can help to push out the frontier (Djankov, McLiesh and Shleifer, 2007, among others). It
is important to note that these market-developing policies are long-term in nature, as they
do not only involve deep and often drawn-out political processes, but their benefits also
materialize over a longer horizon.
Market-enabling policies help push a financial system closer to the frontier, and
include more short- to medium-term policy and regulatory reforms. For instance, policies
aimed at fostering greater competition can result in efficiency gains, as illustrated, by the
recent vigorous expansion of profitable micro- and consumer lending across many
developing countries. Such policies can also include removing regulatory impediments
10
For instance, deposit mobilization and credit expansion in transition economies only took off when
disinflation became entrenched (IMF, 2012).
19
and reforming tax policies. 11 Enabling policies are not just limited to allowing new entry
and facilitating greater contestability, but also include “activist” competition policies, such
as opening up infrastructures (e.g., payment systems and credit registries) to a broader set
of institutions, or forcing institutions to share platforms and infrastructure. Beyond
targeting competition, market-enabling policies can address hindrances such as
coordination failures, first mover disincentives, and obstacles to risk distribution and
sharing in financial markets. While these government interventions can be diverse, they
tend to share a common feature in terms of creating incentives for private lenders and
investors to step in, without unduly shifting risks and costs to the government (e.g.,
providing partial credit guarantee schemes and establishing joint platforms).
A final set of policies aim at preventing the financial system from moving beyond the
frontier (i.e. the sustainable long-term equilibrium.) This set of market-harnessing or
market-stabilizing policies encompass risk oversight and management, and include the
regulatory and supervisory framework, macro-economic and macro-prudential
management. These include upgrading regulatory frameworks to mitigate risks stemming
from increased competition from new non-bank providers of financial services, carefully
calibrating the pace of financial liberalization to the prudential oversight capacity, and
establishing cross-border regulatory frameworks to mitigate risks stemming from
increased international financial integration. Such policies are also important on the user
11
Examples from country experiences abound (IMF, 2012). For instance, the development of the
government bond market in Mexico was spurred by the elimination of compulsory lending to the
government by banks. Similarly, in Turkey, tax reform (e.g., the elimination of withholding tax on income
from bonds with maturities of over five years and reducing the tax rate on those with maturities of less than
five years) and greater transparency served to increase investor appetite for corporate bonds. Similarly,
reducing restrictions on the asset composition of insurance companies in Barbados allowed the industry to
fill an important role as a major supplier of mortgage finance until banks became more active in the market.
20
side (e.g., minimizing the risk of household over-indebtedness, through financial literacy
programs and consumer protection frameworks).
4. Benchmarking – A macro-quantitative approach to identifying the financial
possibility frontier
In this section, we will discuss how the concept of a financial depth frontier can be partly
operationalized using the benchmarking exercise developed by Beck et al. (2008) and De
la Torre, Feyen and Ize (2013). Specifically, using a large cross-country panel, a time-
variant benchmark for different financial sector indicators can be constructed by using the
predicted value of regressions of financial sector indicators on an array of country
characteristics proxying for the different frictions discussed above (e.g., income, size,
population density, and demographic structure). As discussed by Barajas et al. (2013), this
benchmark is not the equivalent to the frontier as it does not take into account long-term
and deep-rooted institutional characteristics of countries. Including specific institutional
measures raises (i) concerns of endogeneity of such measures to the specific financial
system outcome variable and (ii) measurement concerns about the institutional
indicators. 12 Rather, we can see this benchmark as representing a structural depth line,
i.e. the level of financial development predicted by structural country characteristics that
are not directly related to policies and/or the financial sector. The gap between the actual
and predicted level of financial development can then be related to different policies.
The benchmarking exercise estimates the following regression
12
One can also interpret GDP per capita, one of the explanatory variables, as capturing institutional quality
on a very general level, as it is empirically highly correlated with general institutional quality indicators, as
those by Kaufman, Kraay and Mastruzzi (2011).
21
FDi,t = βXi,t+εi,t (1)
where FD is the log of an indicator of financial development, X is an array of structural
country-specific factors, and the subscripts i and t relate to countries and years,
respectively. The regression includes several country characteristics that theory predicts to
be associated with the level of financial development in a country. First, the log of GDP
per capita and its square (to account for possible non-linearities) proxy for general
demand and supply-side constraints related to low income, Second, the log of population
proxies for market size, in line with the above discussion on scale economies. Third, the
log of population density proxies for geographic barriers and thus the ease of financial
service provision. Fourth, the log of the age dependency ratio is included to capture
demographic trends and corresponding savings behavior. Finally, dummy variables for
off-shore centers, transition countries and oil-exporting countries are included to control
for specific country circumstances, as these countries face specific challenges and
development experiences that impact their financial systems. 13
Barajas et al. (2013) and De la Torre, Feyen and Ize (2013) use this regression
model to predict a large number of financial sector indicators capturing the depth,
efficiency, stability and outreach of different segment of the financial system, including
banking, capital markets and contractual savings institutions. While results vary and
significance levels are influenced by the number of data points available, the regression
models confirm the importance of the socio-economic indicators included as explanatory
variables. The benchmarking exercise also confirms the predictions of the frontier
concept, as the gap can be explained by an array of macroeconomic, regulatory,
13
In related work, Buncic and Melecky (2013) show substantial cross-country heterogeneity in the estimated
level of equilibrium credit, due to differences in financial structure and regulatory frameworks.
22
institutional and market structure variables. Specifically, Barajas et al. (2013) relate the
gap between predicted and actual financial development, as measured by Private Credit to
GDP to an array of policies and institutions. Their results suggest that lower inflation,
higher remittance share, and higher previous rates of growth all are associated with lower
gaps between predicted and actual levels of Private Credit to GDP, as are a lower share of
government ownership, better banking supervision, and stronger creditor rights.
Restrictions on foreign bank entry, greater exchange rate flexibility, and gross capital
inflows are associated with higher gaps, while greater competition and overall financial
reform are related to lower gaps between predicted and actual levels of Private Credit to
GDP. Barajas et al. (2013) also show that rapid changes in Private Credit to GDP, relative
to its predicted benchmark, are related to boom-and-bust cycles and thus ultimately bank
fragility.
How can comparisons of the actual level of financial development with the
predicted level help in the assessment of a financial system, in assessing whether a
financial sector is “too hot, too cold or just right”? If the actual level of financial
development is below the predicted level (thus a positive Gap), several additional
empirical analyses can give insights into the reasons. First, what are the macroeconomic
and institutional conditions for financial deepening in the country? High and volatile
inflation and a deficient institutional framework (limited creditor rights that are not being
enforced, lack of credit information sharing) can depress the sustainable constrained
equilibrium (i.e. frontier) below the structural depth line. Second, there might also be
demand-side constraints, related to a previous boom-bust cycle and the consequent burden
of over-indebtedness for both enterprises and households. Third, there might be barriers
23
related to market entry or regulatory constraints that prevent the financial system from
deepening. Analysis of the market structure and degree of competition in the financial
system might be useful in that context.
If the actual level of financial development is above the predicted level, this can
also be due to several reasons, which can be gauged with different data sources. First, a
sound and flexible institutional framework might allow the financial system to move
beyond its structural depth line. If this movement beyond the predicted level has been a
gradual one and in line with improvements in policy and institutional indicators, it might
be indeed sustainable. If on the other hand, there is a rapid increase in financial depth
indicators such as Private Credit to GDP, concentrated in specific sectors, such as
household or mortgage credit or in foreign currency rather than local currency, this might
indicate an unsustainable expansion. Finally, bailout expectations as gauged from banks’
credit ratings and funding cost differences between systemically important banks and non-
systemic institutions might give additional indications of overheating.
The benchmarking exercise can also be used to gauge the differential development
of different segments of the financial system, as done by De la Torre, Feyen, and Ize
(2013) who apply a quantile regression framework to a global panel database to explain
the variation in a large set of financial indicators. The model’s independent variables
consist of structural country factors including demographic factors (population size and
density) and dummy variables for specific country circumstances (fuel exporter status,
transition country indicator, and an offshore center indicator) and a set of year indicators.
In addition, the model includes economic factors that are decomposed into an initial
income effect, a contemporaneous economic growth effect, and the interaction between
24
these two factors. This approach allows for the association of economic development with
financial indicators to be dependent on the economic development path of the country.
More formally, the specification of the benchmark model is:
(2)
where FDti , j is the (log of) the financial development indicator j for country i at time t, sti
is the (log of) the country’s population size, Xti is a vector of the remaining country-
specific structural characteristics, and Zti is a vector of policy variables.
A large α 1 coefficient implies that the financial indicator is more strongly
associated with a country’s initial level of income (measured by log GDP per capita in
1980), suggesting that the associated financial activities develop when a country is
economically more sophisticated. Similarly, the α 2 + α 3 y0 term captures the sensitivity of
the financial indicator to economic growth. The larger this term, the more strongly
associated financial activities will increase as a country grows faster. Finally, the α 4
coefficient measures the return to scale of the financial indicator.
Table 1 presents the regression results and shows that the benchmark model is able
to explain a significant portion of the variation for many financial indicators. In particular,
a key finding is that population scale effects are significant for most financial indicators.
The regressions also show that fuel exporters and transition countries typically lag behind
while offshore centers tend to be ahead. As regards their association with economic
development, all financial indicators are significantly and positively associated with initial
income. In addition, financial indicators also show significant variation in their sensitivity
to economic growth. In particular, the impact of initial income on the magnitude of the
25
economic growth effect various across indicators and, combined with the secular growth
effect, gives rise to financial development paths of various shapes. For example, the
economic growth effect is strong for bank credit whereas initial income does not play a
large role since the interaction term is insignificant. In contrast, for some indicators such
as mutual fund assets, initial income has a very large, positive impact on the economic
growth effect (i.e. the interaction term is positive and significant) whereas the secular
economic growth effect is negative. This implies that countries at a low level of economic
growth and initial income will typically exhibit weakly developed mutual funds.
Table 2 presents benchmark regressions which add four contractual and
informational policy factors to the basic model (strength of legal rights, quality of credit
information, strength of investor protection index, and contract enforcement costs). To
proxy for the quality of the macro-prudential management, a credit crash dummy is
included which captures severe drops in private credit to GDP levels. The explanatory
power of the model increases noticeably for most financial indicators, confirming that
policy matters. As such, the expanded benchmark model produces a closer proxy to the
financial possibility frontier. The regressions show that the policy factors are significantly
associated with most financial indicators. As expected, some policy factors matter more
for some dimensions of financial sector development than for others. For example, better
creditor rights appear to promote bank credit, capital market development, and life
insurance. Similarly, lower enforcement costs facilitate bank lending and lower net-
interest margins. Weak macro-prudential management not only affects bank credit, but
also other financial indicators such as pension fund assets and life insurance premiums.
26
TABLE 1. Basic Benchmark Regressions
Panel A
Bank Claims Bank Credit Bank Bank Non- Insurance Insurance
Bank Private Net Interest
On Dom. To Domestic Deposit Premiums Premiums
Credit Margin
Fin. Sector Government Deposits Funding (Life) (Non-Life)
1 2 3 4 5 6 7 8
Log Initial GDPPC 0.372*** −0.261*** 0.822*** 0.285*** 0.288*** 0.380*** 0.619*** 0.267***
Log GDPPC minus Log
0.840*** 0.120 −0.286 1.634*** 1.535*** −0.271 0.745** −0.155
Initial GDPPC
Interaction 7.95e−05 −0.0837*** 0.223*** −0.183*** −0.0964*** 0.146*** 0.133*** 0.0686***
Log Population 0.0721*** −0.0660*** 0.243*** 0.0940*** 0.0367*** 0.0717*** 0.0424** −0.0496***
Log Population 0.0193*** −0.0293*** 0.339*** 0.200*** 0.0870*** 0.0452*** 0.0999*** −0.0403***
density
Fuel dummy −0.272*** 0.00729 −0.256*** −0.262*** −0.163*** −0.0551 −0.687*** −0.202***
Offshore dummy 0.331*** 0.105** −0.634*** 0.166*** 0.333*** 0.428*** −0.130 0.107**
Transition dummy −0.0350 0.187*** −0.102 −0.0864 −0.170*** 0.220*** −0.779*** −0.0863*
Constant 0.285*** 3.709*** −8.413*** −1.285*** 0.815*** −0.441*** −6.126*** −1.708***
Observations 4,075 1,785 1,643 4,003 4,097 3,983 2,138 2,308
2
Pseudo R 0.388 0.294 0.247 0.141 0.401 0.285 0.384 0.357
Panel B
Stock Market Domestic Domestic Foreign Foreign
Pension Mutual Fund Stock Market
Capitalizatio Private Debt Public Debt Private Debt Public Debt
Fund Assets Assets Turnover
n Securities Securities Securities Securities
1 2 3 4 5 6 7 8
Log initial GDPPC 0.317*** 0.734*** 0.672*** 0.415*** 1.010*** 0.159*** 1.030*** −0.134***
Log GDPPC minus
Log initial GDPPC −3.501** −1.423*** 1.853*** 0.253 2.332*** 0.0639 −0.426 −2.144***
Interaction 0.566*** 0.472*** −0.0452 0.0900 −0.0578 −0.0207 0.239*** 0.167**
Log population −0.0994 0.135*** 0.462*** 0.118*** 0.112*** 0.0973*** 0.122*** −0.243***
Log population
density −0.152*** 0.00934 0.0661*** 0.0756*** −0.131*** 0.0571*** −0.0115 −0.253***
Fuel dummy 0.360** −0.224** −0.0575 0.0716 −0.785*** −0.357*** 0.0507 −0.00290
Offshore dummy −0.278 0.960*** −0.592*** 0.391*** −0.0158 −0.345*** 0.150 −0.0280
Transition dummy −1.834*** −1.421*** 0.722*** −0.669*** −0.504** −0.118 −0.499*** −0.474***
Constant 0.247 −5.554*** −4.359*** −0.975*** −6.488*** 1.579*** −7.983*** 4.601***
Observations 568 613 1,682 1,818 889 978 985 1,198
Pseudo R2 0.169 0.383 0.375 0.274 0.353 0.0808 0.382 0.138
Note: This table displays the median regression results of equation (1) using a panel of country-year data for the 1980–2010 period.
GDPPC stands for gross domestic product per capita.
Source: De la Torre, A., E. Feyen, and A. Ize (2013).
27
TABLE 2. Extended Benchmark Regressions
Panel A
Bank
Bank Net Bank Credit Bank Bank Non- Insurance Insurance
Claims On
Private Interest To Domestic Deposit Premiums Premiums
Dom. Fin.
Credit Margin Government Deposits Funding (Life) (Non-Life)
Sector
1 2 3 4 5 6 7 8
Log initial GDPPC 0.266*** −0.260*** 0.664*** 0.415*** 0.269*** 0.411*** 0.508*** 0.199***
Log GDPPC minus
Log initial GDPPC 0.456*** 0.524*** −0.817 2.065*** 1.049*** −0.378* 0.391 −1.114***
Interaction −0.00235 −0.134*** 0.283*** −0.253*** −0.0817*** 0.115*** 0.0998** 0.187***
Log population 0.0406*** −0.112*** 0.294*** 0.204*** 0.0576*** 0.0754*** 0.0626*** −0.0520***
Log population
density 0.0465*** −0.0167 0.348*** 0.175*** 0.0623*** 0.0152 0.139*** −0.0284***
Fuel dummy −0.233*** −0.0135 0.289* −0.464*** −0.227*** −0.145*** −0.519*** −0.183***
Offshore dummy 0.271*** 0.00753 −0.767*** 0.157* 0.362*** 0.675*** −0.195* 0.0437
Transition dummy −0.373*** 0.152** −1.572*** −0.146 −0.319*** −0.118 −1.645*** −0.272***
Private credit crash −5.963*** 2.945*** −3.188** −1.724*** −3.329*** −5.281*** −1.782*** −0.409
Strength of legal
rights index 0.0288*** −0.00336 0.242*** −0.0454*** 0.00687 0.0178* 0.277*** 0.0561***
Credit information
index 0.0425*** 0.0857*** −0.0264 −0.210*** −0.0449*** −0.0560*** 0.0546*** 0.0180**
Strength of investor
protection index 0.0167 0.0103 −0.0933* 0.155*** 0.0570*** −0.0390** −0.0250 −0.0414***
−0.00326** −0.00238** −0.00378** 0.00668**
Enforcement costs * 0.00178** −0.00486* −0.00268** * * * 0.000972
Observations 2,148 1,731 1,056 2,140 2,160 2,094 1,805 1,857
Pseudo R2 0.710 0.479 0.395 0.317 0.662 0.604 0.633 0.537
27
28
Panel B
Stock Domestic Domestic Foreign
Pension Mutual Stock Foreign
Market Private Public Private
Fund Fund Market Public Debt
Capitaliza Debt Debt Debt
Assets Assets Turnover Securities
tion Securities Securities Securities
1 2 3 4 5 6 7 8
Log initial GDPPC −0.0629 0.713*** 0.593*** 0.481*** 1.173*** 0.346*** 1.006*** −0.224***
Log GDPPC minus
Log initial GDPPC −2.166 −2.300*** 1.268*** 0.644* 5.861*** 1.311** −0.894 −1.431**
Interaction 0.285 0.476*** −0.0795 −0.000579 −0.487*** −0.224*** 0.327*** 0.133
Log population −0.0525 0.287*** 0.619*** 0.155*** −0.0301 0.154*** 0.123*** −0.467***
Log population
density −0.142*** −0.119*** 0.00520 0.0397** −0.0740* 0.129*** −0.0179 −0.184***
Fuel dummy 0.182 −0.335** −0.183** 0.0137 −0.380*** −0.00603 0.0845 −0.0817
Offshore dummy 0.121 1.230*** −0.334*** 0.0959 −0.567*** −0.509*** −0.243* −0.478***
Transition dummy −3.052*** −1.387*** 0.635*** −0.926*** −0.744** 0.359* −0.673*** −0.460***
Private credit crash −5.985*** −7.414*** −6.495*** −4.187*** 4.262** −2.988** −0.742 8.200***
Strength of legal
rights index 0.189*** 0.000925 0.00960 0.0372** 0.176*** −0.0530** 0.0421* −0.0906***
Credit information
index 0.275*** −0.324*** −0.0881*** −0.132*** 0.181*** 0.108*** −0.111*** 0.115***
Strength of investor
protection index 0.0476 0.0617 0.157*** 0.121*** 0.0480 0.0952*** −0.0470 −0.0532
Enforcement costs −0.00971 −0.00576 −0.0127*** 0.00268 0.00390 −0.00294 0.00623** −0.00164
Observations 565 567 1,292 1,344 645 707 883 1,073
Pseudo R2 0.378 0.669 0.598 0.490 0.567 0.277 0.617 0.330
Note: This table extends table 1 by adding the following additional policy variables: Private credit crash (which
assumes a value of 1 if private credit to GDP drops by over 20 percent for a particular country-year) and a set of
variables taken from the World Bank Doing Business Database, including the Strength of legal rights index (the
extent to which creditors are legally protected), the Credit information index (the quality of credit information),
the Investor protection index (the extent to which investors are protected by law), and Enforcement costs (the
cost to enforce a contract). The contract enforcement index is the first principal component of the following
indicators (also from Doing Business): contract enforcement costs, number of days to enforce a contract (in
logs), and number of procedures to enforce a contract. GDPPC stands for gross domestic product per capita.
***, **, and * indicate p < 0.01, p < 0.05, and p < 0.1
Source: De la Torre, A., E. Feyen, and A. Ize (2013).
28
29
The sequential development of different segments illustrated with these benchmarking
regressions is also confirmed by the financial structure literature that shows that economically
and financially more developed countries tend to have more market-based financial systems,
i.e. financial systems where capital markets have a more prominent role in enterprise
financing (Demirguc-Kunt and Levine, 2001). Similarly, Beck et al. (2012) show that
economically and financially more developed countries channel a larger share of its bank
lending to households rather than enterprises.
While the concept of the financial possibility frontier and the taxonomy of financial
sector policies that it helps define can be an important guiding principle for financial sector
policy reforms, two caveats should be borne in mind. First, given the uniqueness of
macroeconomic, institutional, and structural conditions and the incidence of leapfrogging and
financial crises, financial deepening paths may not necessarily be replicable across countries.
The focus here is on identifying policies that have played a role in pushing financial systems
towards the financial possibility frontier or shifting the frontier outwards. Second, the
considerable heterogeneity within developing countries implies that while the reforms
discussed are relevant across a broad range of countries, their relative importance and cost-
benefit tradeoffs can differ widely across countries and even the same country over time,
pointing to the need to account for country-specific circumstances and institutions.
5. From shallow markets to overheating – Applying the frontier concept to transition
economies
This section applies the frontier concept to one specific region – the former transition
economies of Eastern Europe and Central Asia - and illustrates how the concept can be used
to both identify positions below the frontier and above the frontier.
29
30
5.1. The challenges at transition
While we can observe many different patterns of financial sector development across
countries and over time, the process of financial deepening over the last 20 years of transition
in Central and Eastern Europe and Central Asia has shown some striking differences to
financial system development in other parts of the world. First, the transition economies had
to start almost from zero in developing market-based financial service provision, but with a
legacy of non-performing loans to state-owned enterprises. In the context of the frontier,
concept, transition economies thus faced adverse structural state variables at the outset of the
transition process. Second, financial sector development was part of a larger structural
transformation of countries from centrally planned towards market-based economies. Third,
even more than in other countries, financial sector policies were closely linked to
macroeconomic, institutional and political choices governments had to make in the early days
of transition. The result of these interlinkages was that rather than an agent of transformation
and development, financial institutions and markets were as much affected by the path and
speed of reform as the real sector, most prominently their borrowers. While financial sector
development was not simply the result of the transformation process and economic growth
either, the paths of economic, institutional and financial development were co-determined by
a choice of reform policies during the first years of transition.
5.2. Moving towards the frontier
Twenty years after the start of transition, financial systems in the transition economies
have developed from mono-bank systems into market-based financial systems. However,
there is a wide variation in financial sector development across different countries within the
region. The financial deepening process across the region and over time can be best
appreciated comparing the actual level of financial development with the predicted one, using
30
31
the benchmarking model discussed above. Figure 3 plots the predicted and actual value of
Private Credit of the median transition economy for the period 1995 to 2011. While in the
early part of the sample period the actual value was below the predicted value, the actual
value pulled ahead of the predicted value in the 2000s. In 2003, the two lines crossed, with
subsequent rapid increase in Private Credit to GDP.
Figure 3: Private Credit to GDP relative to a benchmark across transition economies
50
45
40
35
30
25 Private Credit to GDP
20 benchmark
15
10
5
0
1995 1997 1999 2001 2003 2005 2007 2009 2011
Source: Global Financial Development Indicators, own calculations
The deepening process went hand in hand with an institutional upgrade, as illustrated
in Figure 4, gauged by Doing Business Indicators. Specifically, the rights of creditors and
investors increased, while the largest increase can be observed in the credit registry index.
Most countries introduced credit registries or upgraded them significantly in the 2000s, with
significant effects on firms’ access to credit (Brown, Jappelli and Pagano, 2009). However,
other dimensions of the institutional framework only improved little or not at all, at least in
the median transition economy. Specifically, Figure 5 shows that the bankruptcy recovery
rate improved only slightly, while the cost of property registration dropped slightly and the
cost of contract enforcement actually increased in the median country.
31
32
Figure 4: Development of institutional infrastructure across transition economies
8
7
6
Strength of legal rights
5
index (0-10)
4 Depth of credit
information index (0-6)
3
Strength of investor
2 protection index (0-10)
1
0
2004 2005 2006 2007 2008 2009 2010 2011 2012
Source: Doing Business, own calculations
Figure 5: Development of institutional costs across transition economies
40
35
30
Cost (% of claim)
25
20 Recovery rate (cents
on the dollar)
15
Cost (% of property
10 value)
5
0
2004 2005 2006 2007 2008 2009 2010 2011 2012
Source: Doing Business, own calculations
In addition, the financial possibility frontier has also been pushed by improvements in
macroeconomic stability, socio-political stability in many though not all transition economies
and by foreign bank entry. While often controversial, the evidence on the effect of foreign
bank entry on the efficiency, breadth, and stability of banking systems in transition
economies has been overwhelmingly positive. Perhaps the most important impact of foreign
32
33
bank entry was on cutting entrenched relationships between politically connected enterprises
and the banking system (Gianetti and Ongena, 2009). Foreign bank entry was a critical
element of the disciplining framework that countries in Central Europe put in place in the mid
to late 1990s and set them on a path to financial deepening.
The increase in financial depth, including Private Credit to GDP was accompanied by
increase in the share of enterprises that finance their investment with bank credit, as gauged
by the World Bank Group’s Enterprise Surveys. Specifically, this share increased from 14
percent in 2002 to 28 percent in 2005 to 36 percent in 2008/9. This increase in access to
financial services has been confirmed by in-depth studies and has also been linked to specific
institutional upgrades (Brown, Jappelli and Pagano, 2009, Gianetti and Ongena, 2009).
5.3. Moving beyond the frontier
However, the benchmarking exercise might have also given first indications of an
overheating in the mid-2000s. Specifically, while both actual credit and deposit to GDP
ratios moved beyond the predicted levels, the credit increase was faster than the deposit
increase, ultimately resulting in an “intermediation efficiency” ratio of credit to deposit above
one. The ratio of credit to deposits moved beyond its predicted level after 2003 (Figure 6).
Much of this additional credit was allocated to households rather than enterprises, especially
in the form of mortgage credit for longer maturities in some cases in foreign currency
(Figures 7 and 8).
33
34
Figure 6: Credit-deposit ratio across transition economies over time
160
140
120
100
80 Credit-Deposits
60 Benchmark
40
20
0
1995
1996
1997
1998
1999
2000
2001
2002
2003
2004
2005
2006
2007
2008
2009
2010
year
Source: Global Financial Development Indicators, own calculations
Figure 7: Household credit across transition economies over time
Figure 1: Total Household Credit to Households, 1995-2007
60
40
(% of GDP)
20
0
1995 1997 1999 2001 2003 2005 2007
Bulgaria Croatia Czech Republic Estonia
Hungary Latvia Lithuania Poland
Romania Slovak Republic Slovenia Turkey
EU-15 and Cyprus
Source: Allen et al. (2011)
Figure 8: Mortgage credit across transition economies over time
Figure 2: Mortgage Credit to Households,1995-2007
80
(% of Total Household Credit)
60
40
20
0
1995 1997 1999 2001 2003 2005 2007
Bulgaria Croatia Czech Republic Estonia
Hungary Latvia Lithuania Poland
Slovak Republic Slovenia Turkey EU-15 and Cyprus
Source: Allen et al. (2011)
34
35
While aggregate indicators pointed to a boom, there were also more detailed bank-
level data that pointed to a movement beyond the frontier, i.e. towards an unsustainable level,
including a shift towards foreign currency lending. In 2008, the share of foreign currency
debt in total debt ranged from less than 20% in the Czech Republic to over 47% in Lithuania
(Allen et al., 2011). Obvious (at least ex-ante) arbitrage possibilities were exploited by banks
and households, taking out Swiss Franc or Euro mortgages as lower interest rates than local
currency mortgages, betting on the seemingly unavoidable long-term appreciation of local
currencies, following the Balassa-Samuelson hypothesis. This trend towards both foreign-
currency loans in many countries thus took the character of carry trades for consumers and
producers of non-tradables. While the offer of mortgages in Euros and Swiss Francs was for a
long time seen as innovation, allowing households to directly benefit from these seemingly
riskless arbitrage possibilities, this also exposed them to currency shocks.
In addition, there were also macroeconomic warning signs, pointing to aggregate
imbalances that had been observed earlier in the lead-up to banking and currency crises
(Berglöf et al., 2009, Sirtaine and Skamnelos, 2007). This included a private sector deficit
and lack of savings, which could be interpreted as an overshooting in dis-savings after the
transition, ultimately resulting in negative net asset positions (Figure 9).
Figure 9: Net foreign currency asset as share of GDP
30
20 Bulgaria
10
Czech
0 Republic
-10 2000 2005 2008 Estonia
-20 Hungary
-30
Latvia
-40
-50
-60
Source: Mihaljek (2009)
35
36
While warning signs were increasingly obvious in 2007/2008, it was ultimately the
exogenous shock of the Global Financial Crisis that pushed the financial systems of many
transition economies into reversal exposing the buildup of financial sector vulnerabilities
suggesting that several countries in the region were unequivocally operating beyond the
financial frontier.
This section showed how the benchmarking exercise building on the frontier concept
plus an analysis of the institutional framework underpinning financial sector development can
be used to gauge financial sector development. It clearly shows that there can be too much of
a good thing, i.e. a movement of financial sector deepening beyond the frontier, captured by
aggressive expansion trends in the banking system as well as funding and asset structure of
banks.
6. Application of the frontier concept using micro-data – Benchmarking SMEs’
financing constraints
The frontier concept can be also applied to specific markets and client groups, such as the
SME credit market. Across the globe, SMEs suffer from higher financing obstacles than
large corporate and have more limited access to external sources of finance. As discussed in
detail by Beck and de la Torre (2007), the frontier concept can be used to derive an access
possibilities frontier for SMEs. We will summarize their arguments briefly in the following
and discuss an empirical application.
6.1. Deriving the access possibilities frontier
Transaction costs and information asymmetries drive the variation in access to finance
across firms of different sizes. Fixed transaction costs in credit assessment, processing, and
monitoring result in a decrease of unit costs as the size of the loan increases, which makes
36
37
lending to SMEs more costly. In addition to transaction costs, SME lending, more than other
lending products, is affected by challenges in managing risks. Compared with large firms,
SMEs are commonly less likely to be able to post collateral, have less formal governance
structures, and often do not have audited financial statements that allow a better picture of the
enterprise and its projected profits. Compared to retail clients, financial institutions can rely
less on the law of large numbers to exploit scale economies and diversification benefits in the
case of SMEs as there are fewer of them in a given sector and their characteristics are harder
to capture in a few quantitative indicators. 14
Lending techniques, government policies and structural characteristics of financial
systems and economies affect the extent to which transactions costs and risk reduce SMEs’
access to external funding. We define as the access possibilities frontier the maximum share
of SMEs applying for loans that can be served by financial institutions in a commercially
viable way (see Figure 10, Point I, A). 15 This concept implies that, in many economies, a large
share of micro-enterprises and even small formal firms might not be bankable from a
commercial viewpoint. This frontier—and thus the share of bankable SME loan applicants —
is determined by the state variables we have discussed above, including available lending
technologies, risk management facilities (such as availability of hedging and securitization
16
instruments), credit registries and the contractual framework. Please note that the shape of
this frontier is somewhat different from the previous, more general and aggregate, analysis, as
14
See Beck and de la Torre (2007) and de la Torre, Martinez Peria and Schmukler (2010) for a more in-depth
discussion and references.
15
As discussed in more depth in Beck and de la Torre, (2007), the fact that there is no unique combination of
costs, expected return, and risk that maps one-to-one to the interest rate limits our graphical analysis to loan
applicants as opposed to all potential borrowers.
16
The supply curve underlying this concept is non-linear and can bend backward. i* denotes the marginal
interest rate at the rationed equilibrium rather than the market-clearing equilibrium. For a detailed technical
discussion on the derivation of these curves, we would like to refer the reader to Beck and de la Torre (2007).
37
38
we plot the frontier here in the outreach-price space, where the state variables –both structural
and policy – are incorporated in location and shape of the frontier curve.
Figure 10: Access possibilities frontier for credit
Source: Beck and de la Torre (2007)
Figure11: Access possibilities frontier for credit – changes in state variables
Source: Beck and de la Torre (2007)
Similar to the discussion on the financial possibility frontier, we can use the access
possibilities frontier to identify several types of access to credit problems. A first type of
access problem is demand-originated. This problem may be evident in too low a number of
loan applicants simply because of self-exclusion resulting from cultural barriers or financial
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illiteracy. Alternatively, there may be a lack of profitable investment projects in the economy
that deserve financing based on their expected return. This problem can actually not be
illustrated in our figure as it focuses on loan applicants. A second type of access problem can
arise from regulatory distortions or insufficient contestability that cause lenders not to fully
exploit all the outreach opportunities and thus settle at a point below the access possibilities
frontier with a higher marginal interest rate (Figure 10, Point II, B). A third and very
different access problem is associated with “excess access,” that is, an equilibrium above the
access possibilities frontier with loans being granted to a larger share of loan applicants than
is prudently warranted or SMEs achieve too high a leverage, given the lending interest rate
and the institutional framework (Figure 10, Point III, C). A final access problem consists of
too low a prudent access possibilities frontier, caused by deficiencies in an economy’s
institutional framework compared with that of countries with similar levels of economic
development. An improvement along these lines would lead to an expansion of the frontier
from S* to S*’’ in Figure 11. Similarly, lower opportunity costs of funding (imc), e.g. due to
better macroeconomic conditions, will increase the universe of potential loan applicants
receiving finance (Figure 11, Point II, B).
6.2. Matching the concept with data
As in the case of aggregate indicators, the frontier concept can be matched with
empirical data. First, using the benchmarking model described above, one can predict the
share of (small) firms with access to a credit line or loan by a formal financial institution and
compare them to the actual share, as gauged by the Enterprise Surveys, undertaken by the
World Bank/IFC. Figure 12 graphs the gap between the predicted and the actual share of
small enterprises that use a credit line or loan from a formal financial institution. There is a
large variation, ranging from Serbia, where the predicted is 44 percentage points above the
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40
actual share of small enterprises with a formal loan, to Slovenia, where the actual level is 29
percentage points below the predicted level.
Figure 12: Gap in share of small firms with formal credit across countries
gap_small
50
40
30
20
10
gap_small
0
Bosnia and …
Micronesia, Fed. …
Argentina
Slovenia
Lesotho
Serbia
Azerbaijan
Brazil
Poland
Chad
Hungary
Nicaragua
Indonesia
Czech Republic
Slovak Republic
Bhutan
Russian Federation
Malawi
-10
-20
-30
-40
Source: Enterprise Surveys, own calculations
The Enterprise Surveys, however, also allow a deeper look into the reasons of why
firms do not use formal financial services, i.e. whether there are demand-side or supply-side
constraints. Table 3 provides an example, comparing low and lower-middle income countries
in and outside Sub-Saharan Africa (Beck and Cull, 2014). There is not only a smaller share
of firms that have a loan in Africa than outside Africa, but among those firms without a loan,
a smaller share of firms applied for a loan in Africa than outside Africa. Considering the
reasons for not applying for a loan sheds lights into the bottlenecks that prevent the SME
financing frontier from moving outwards in Africa. First, complex application procedures
and high collateral requirements point to supply-side constraints, caused either by
institutional deficiencies (such as non-existing or ineffective collateral and credit registries)
or inefficiencies within the banking system. A higher share of enterprises in Africa points to
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41
complex application procedures and high collateral requirements than in non-African
countries. The share of non-applying firms pointing to complex application procedures is
especially high (above 30%) in several West and Central African countries, including Benin,
Burkina Faso, Central African Republic, Cameron, Cape Verde, Mali, and Niger, but also
Lesotho and Rwanda. The high share of non-applicants pointing to complex application
procedures as constraint might be associated with high documentation requirements of
regulators, but also a more formalistic approach by banks. Similarly, high collateral
requirements are quoted as reasons for not applying especially in Burkina Faso, Cameron,
and Ethiopia, which might be related to the limited enforceability of collateral in case of loan
default. Fourteen percent of firms in Africa point to high interest rates as reason for not
applying, compared to only 10 percent outside Africa. Second, high interest rates as reason
for not applying can be due to macroeconomic instability, such as in Zimbabwe (several
years of rampant inflation) or high risk premia (DRC). Third, the size of loan or too short a
maturity are rarely given as reason for not applying, while the need to pay bribes is
mentioned by four percent of non-applicants in Africa and is especially high in Cote d’Ivoire,
Ethiopia, Sierra Leone, and Zimbabwe. Matching these constraints as expressed by non-
applicants across countries with supply-side constraints in the policy framework (e.g.,
contractual and collateral frameworks, existence and efficiency of credit registries and
macroeconomic stability) and market structure and competition in the banking system allows
a clear identification of state variables that keep the access frontier too low but also more
short-term policy bottlenecks that prevent the financial system to move towards the frontier.
Finally, there might be demand-side reasons for not applying related to the lack to
investment projects or expansion possibilities, as already discussed above. Notably, a smaller
share of non-applicants points to no need as reason for not applying in Africa compared to
non-African developing countries, pointing to a smaller role for demand-side constraints.
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However, across African countries, the share of non-applicants stating no need as reason for
not applying varies a lot, ranging from 15 percent in Cote d’Ivoire to 85 percent in Eritrea.
Table 3: Demand and supply constraints prevent enterprises from loan applications
Do you have a loan?
yes no
16.52 83.48
28.64 71.36
Did you apply for a loan?
Region yes no
Africa 27.76 72.24
Rest of the World 30.56 69.44
Why did
you not
apply?
Africa Rest of the world
no need for a loan 43.24 62.22
application procedures are complex 15.91 7.05
interest rates are not favorable 14.03 10.27
collateral requirements are too high 9.01 4.28
size of loan or maturity are insufficient 2.05 1.15
necessary to make informal payments to g 3.77 2.02
did not think it would be approved 7.76 7.10
Source: Enterprise Surveys, own calculations
In summary, firm-level survey data provide insights into the constraints for SMEs’
access to external finance. Combining such data with bank-survey data on lending
constraints (as done, e.g. by the EBRD across transition economies and for individual
countries, such as Kenya and South Africa), loan portfolios and interest rates, and with
institutional data from Doing Business and macroeconomic data can provide valuable
insights into the location of the SME access possibility frontier relative to the actual provision
of SME lending and the policy gaps that makes the two differ. Similar analyses could be
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43
undertaken on the household side, using similar information from the Global Findex database
(Demirguc-Kunt and Klapper, 2013).
7. Egypt – Applying macro and micro data to identify a financial system’s position 17
Macro and micro data can give different and sometimes contradictory insights, as we will
highlight in the following for the case of Egypt.
7.1. Background
Egypt has undergone significant financial sector reform in the mid-2000s that aimed
at making the financial system not only more stable but also more efficient. The reforms
included privatization of one of the four commercial state-owned banks and financial,
operational and institutional restructuring of the remaining three government-owned banks.
The banking sector experienced a consolidation process driven by higher minimum capital
requirement and by the exit of several weak banks, with the number of banks dropping from
57 banks in 2004 to 29 in 2010. Bank supervision has undergone significant changes, moving
from a compliance-based toward a risk-based system. As a result of the reform program,
Egypt’s financial system transformed itself over the past seven years, becoming more stable,
mostly due to addressing loan losses in state-owned banks, increase in provisioning and
capital and the aforementioned increase in minimum capital. There has also been progress in
the financial infrastructure, most notably through the establishment of the credit bureau I-
Score as well as improvements in the payment system. In 2007, a second-tier market – Nilex
- was established by the government to offer funding to SMEs by offering relaxed listing
rules.
17
This section relates to early work by the two authors for an internal World Bank report on Egypt’s post-
revolution challenges in the financial sector.
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44
7.2. Gauging Egypt’s financial system with aggregate data
Today, Egypt’s financial system is relatively large, in comparison to most peer
countries. The benchmarking exercise discussed above shows a financial system
corresponding to its level of income per capita and other country characteristics including
size, population density and demographic structure. Specifically, Figures 13 and 14 show the
actual and predicted values of two aggregate financial depth indicators, corresponding to the
two sides of banks’ balance sheets – Bank Deposits to GDP and Private Credit to GDP.
Figure 13: Deposit collection in Egypt over time
Domestic Bank Deposits / GDP (%)
90.0
80.0
70.0
60.0
50.0
40.0
30.0
20.0
10.0
0.0
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Value Observed Expected median
Source: Global Financial Development Indicators, own calculations
Figure 13 shows that the level of saving mobilization by the banking system has been
higher than predicted by country characteristics, although the gap has been recently closing.
We also note that the level of Bank Deposits to GDP has actually decreased over the past
years. Figure 14 shows that the actual value of Private Credit to GDP has also been above the
predicted value for many years, but has moved below it for 2009, both due to the drop in the
actual level of private sector lending as to the increase in the expected value. The progress
made in financial sector reform has thus not been reflected yet in aggregate financial sector
indicators. While savings mobilization as captured by Bank Deposits to GDP has stagnated,
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45
private sector lending actually declined. This can be explained by the fact that banks started
building provisions and tightening their procedures and controls in response to regulatory
pressures. Notwithstanding this caveat and while quantity is certainly not be equated with
quality, the lack of a medium-term increase in Private Credit to GDP following the financial
sector reform programs is somewhat disappointing and matches the development of demand-
side indicators, as we will discuss below.
Figure 14: Private Credit to GD in Egypt over time
Private Credit / GDP (%)
60.0
50.0
40.0
30.0
20.0
10.0
0.0
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Value Observed Expected median
Source: Global Financial Development Indicators, own calculations
7.3. Gauging Egypt’s financial system with micro-data
While aggregate data and following the benchmarking model described above paint a
favorable picture of Egypt’s financial system, with actual levels well above predicted levels,
micro-level indicators paint a different picture. Figure 15 shows that the share of firms with a
credit from a formal institution has been consistently below the predicted level across three
survey waves (2006, 2008 and 2011). 18 In addition, Figure 16 shows a positive, though non-
linear relationship between the level of Bank Credit to GDP and the share of enterprises that
18
While the gap seemingly closes in 2011, this last survey has to be treated with caution as it relies on a smaller
sample than the two previous surveys.
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46
use credit, with Egypt being a significant outlier. Specifically, corresponding to its level of
Bank Credit to GDP, more than twice as many enterprises should have access to bank credit,
as for example in Cape Verde, which has a similar level of Bank Credit to GDP (42.5%).
Figure 15: Actual and predicted share of firms with credit in Egypt
45.000
40.000
35.000
30.000
25.000 Predicted share of firms
with credit
20.000
Actual share of firms with
15.000 credit
10.000
5.000
0.000
2006 2008 2011
Source: Global Financial Development Indicators, own calculations
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47
Figure 16: Cross-country variation in aggregate credit and share of firms with credit
80.00
Percentage of firms with loan
60.00
40.00
20.00
EGY
0.00
0.00 0.50 1.00 1.50
Bank Credit to GDP
EGY
Other
Fitted values
Source: Global Financial Development Indicators, own calculations
There are several reasons to explain this discrepancy between aggregate and micro-
data. One reason for Egypt being such a big outlier lies in the banking sector focusing
historically on mostly connected lending, based on names or connections, with the large
majority of enterprises being excluded from the formal banking sector and thus puts in
perspective the high value of Private Credit to GDP documented above. This is also
confirmed by considering the share of lending that goes to governments and state-owned
enterprises, which is substantially above its predicted value (Figure 17).
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Figure 17: Credit to Government and SOEs in Egypt over time
Credit to Government and SOEs / GDP (%)
45.0
40.0
35.0
30.0
25.0
20.0
15.0
10.0
5.0
0.0
2002 2003 2004 2005 2006 2007 2008 2009 2010 2011
Value Observed Expected median
Source: Global Financial Development Indicators, own calculations
The example of Egypt shows the importance of considering an array of different data
sources to gauge the efficiency and depth of financial systems. Benchmarking based purely
on aggregate data can be mis-leading if not accompanied by more detailed analysis with
micro-level data.
8. Conclusions
This paper discusses the concept of the possibility frontier as assessment tool for financial
sector development across countries. The financial possibility frontier indicates the
constrained optimum of depth, outreach or breadth of a country’s financial system given
certain state variables that cannot be changed in the short term. We show how the
benchmarking exercise can be used to operationalize the frontier concept on the aggregate
level. We also discuss three examples of how to apply the frontier concept in analytical work.
These three examples are intended to give a flavor of the possibilities that the frontier concept
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49
offers when combined with different data sources. The main conclusions from these three
examples are that only a combination of different data sources – aggregate, demand- and
supply-side – can help to properly identify the frontier, the location of the financial system
relative to the frontier, and the policy constraints that have to be overcome to either help
move a financial system towards the frontier or prevent it from moving beyond to an
unsustainable position.
We see this paper as a first attempt at combining the benchmarking exercise with the
frontier concept and use it as diagnostic tool. The examples we offered were illustrative
rather than conclusive. Future applications could try to derive a frontier for a specific market
segment across countries using a combination of different data sources or try to derive a
frontier for a specific country across different segments using cross-country and country-
specific data and information.
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